Machine Learning Software Engineer Co-op Opportunity at Royal Bank of Canada
3 days ago
We are seeking a highly motivated and enthusiastic software engineer to join our team as a Machine Learning Software Engineer Co-op. As a member of our team, you will be involved in a project end-to-end, from data pre-processing to implementing machine learning algorithms and front-end development.
Our team works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning, and computer vision.
Key Responsibilities- Design and develop machine learning-based software solutions to solve complex problems;
- Collaborate with research and business teams to converge on the best solutions;
- Optimize algorithms and prototypical solutions for efficient implementation;
- Extend prototypes into fully functional, polished solutions ready for internal and/or external use;
- Support projects with thorough documentation of usage, design decisions, and capabilities;
- Extract, transform, and load massive datasets using distributed computing framework technologies (Hadoop, Spark, etc.).
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Software Engineering, or equivalent;
- Experience with software development, including co-op and internships;
- Proficiency in writing software in one of the major languages such as C++, C#, Java, Python;
- Familiarity with the Unix command line and bash scripting;
- Experience with Deep Learning packages such as TensorFlow, Theano, Keras, and PyTorch is an asset;
- Exposure to distributed computing frameworks (e.g., Hadoop, Spark) as well as SQL, NoSQL, and graph databases is an asset.
Royal Bank of Canada is a research institute founded in 2016 by Royal Bank of Canada. Our team of top AI researchers and engineers is motivated by the pursuit of solving intelligence and advancing machine learning science. We utilize the latest AI capabilities to build solutions that address some of the biggest challenges in financial services today.
We are recognized for our industry-leading work around responsible and ethical AI and our commitment to AI innovation, which includes 90+ scientific publications in top-tier academic venues, 105+ patents, and open-source activity. Our research focuses on key areas, including deep learning, time series forecasting, reinforcement learning, explainability, causality, behavioral modeling, and more.
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